tool.py

from smolagents.tools import Tool
import pronouncing
import json
import string

class ParodyWordSuggestionTool(Tool):
    name = "parody_word_suggester"
    description = "Suggests rhyming funny words using CMU dictionary pronunciations."
    inputs = {'target': {'type': 'string', 'description': 'The word you want to find rhyming alternatives for'}, 'word_list_str': {'type': 'string', 'description': 'JSON string of word list (e.g. \'["word1", "word2"]\')'}, 'min_similarity': {'type': 'string', 'description': 'Minimum similarity threshold (0.0-1.0)', 'nullable': True, 'default': '0.5'}, 'custom_phones': {'type': 'object', 'description': 'Optional dictionary of custom word pronunciations', 'nullable': True, 'default': None}}
    output_type = "string"
    RHYME_WEIGHT = 0.5
    PHONE_SEQUENCE_WEIGHT = 0.3
    LENGTH_WEIGHT = 0.2
    PHONE_GROUPS = "M,N,NG|P,B|T,D|K,G|F,V|TH,DH|S,Z|SH,ZH|L,R|W,Y|IY,IH|UW,UH|EH,AH|AO,AA|AE,AH|AY,EY|OW,UW"

    def _get_word_phones(self, word, custom_phones=None):
        """Get phones for a word, checking custom dictionary first."""
        if custom_phones and word in custom_phones:
            return custom_phones[word]["primary_phones"]
        
        import pronouncing
        phones = pronouncing.phones_for_word(word)
        return phones[0] if phones else None


    def _get_primary_vowel(self, phones: list) -> str:
        """Get the primary stressed vowel from phone list."""
        phone_str = ""
        vowel_char = ""
    
        for phone_str in phones:
            if '1' in phone_str and any(vowel_char in phone_str for vowel_char in 'AEIOU'):
                return phone_str.rstrip('012')
        return None


    def _get_phone_similarity(self, phone1: str, phone2: str) -> float:
        """Calculate similarity between two phones."""
        # Initialize variables
        p1 = ""
        p2 = ""
        group_str = ""
        group = []
    
        # Strip stress markers
        p1 = phone1.rstrip('012')
        p2 = phone2.rstrip('012')
    
        # Exact match
        if p1 == p2:
            return 1.0
        
        # Check similarity groups
        for group_str in self.PHONE_GROUPS.split('|'):
            group = group_str.split(',')
            if p1 in group and p2 in group:
                return 0.7
            
        # Check broader categories
        if self._get_phone_type(p1) == self._get_phone_type(p2):
            return 0.3
        
        return 0.0


    def _get_phone_type(self, phone: str) -> str:
        """Get the broad category of a phone."""
        # Strip stress markers
        phone = phone.rstrip('012')
        v = ""
    
        # Vowels
        if any(v in phone for v in 'AEIOU'):
            return 'vowel'
        
        # Initialize fixed sets for categories
        nasals = {'M', 'N', 'NG'}
        stops = {'P', 'B', 'T', 'D', 'K', 'G'}
        fricatives = {'F', 'V', 'TH', 'DH', 'S', 'Z', 'SH', 'ZH'}
        liquids = {'L', 'R'}
        glides = {'W', 'Y'}
    
        if phone in nasals:
            return 'nasal'
        if phone in stops:
            return 'stop'
        if phone in fricatives:
            return 'fricative'
        if phone in liquids:
            return 'liquid'
        if phone in glides:
            return 'glide'
        
        return 'other'


    def _calculate_phone_sequence_similarity(self, phones1: list, phones2: list) -> float:
        """Calculate similarity based on matching phones in sequence."""
        if not phones1 or not phones2:
            return 0.0
    
        # Initialize variables
        total_similarity = 0.0
        i = 0
        similarity = 0.0
    
        comparisons = max(len(phones1), len(phones2))
    
        # Compare each position
        for i in range(min(len(phones1), len(phones2))):
            similarity = self._get_phone_similarity(phones1[i], phones2[i])
            total_similarity += similarity
        
        return total_similarity / comparisons if comparisons > 0 else 0.0


    def _calculate_length_similarity(self, phones1: list, phones2: list) -> float:
        """Calculate similarity based on phone length."""
        max_length = max(len(phones1), len(phones2))
        length_diff = abs(len(phones1) - len(phones2))
        return 1.0 - (length_diff / max_length) if max_length > 0 else 0.0


    def _calculate_similarity(self, word1, phones1, word2, phones2):
        """Calculate similarity based on multiple factors."""
        # Initialize phone lists and scores
        phone_list1 = phones1.split()
        phone_list2 = phones2.split()
        rhyme_score = 0.0
        phone_sequence_score = 0.0
        length_score = 0.0
        vowel1 = None
        vowel2 = None
    
        # 1. Rhyme score (50%) - based on primary vowel
        vowel1 = self._get_primary_vowel(phone_list1)
        vowel2 = self._get_primary_vowel(phone_list2)
        rhyme_score = 1.0 if vowel1 and vowel2 and vowel1 == vowel2 else 0.0
    
        # 2. Phone sequence similarity (30%)
        phone_sequence_score = self._calculate_phone_sequence_similarity(phone_list1, phone_list2)
    
        # 3. Length similarity (20%)
        length_score = self._calculate_length_similarity(phone_list1, phone_list2)
    
        # Combined weighted score
        similarity = (
            (rhyme_score * self.RHYME_WEIGHT) +
            (phone_sequence_score * self.PHONE_SEQUENCE_WEIGHT) +
            (length_score * self.LENGTH_WEIGHT)
        )
    
        return {
            "similarity": round(similarity, 3),
            "rhyme_score": round(rhyme_score, 3),
            "phone_sequence_score": round(phone_sequence_score, 3),
            "length_score": round(length_score, 3),
            "details": {
                "primary_vowel1": vowel1,
                "primary_vowel2": vowel2,
                "phone_count1": len(phone_list1),
                "phone_count2": len(phone_list2),
                "matching_phones": round(phone_sequence_score * len(phone_list1))
            }
        }


    def forward(self, target: str, word_list_str: str, min_similarity: str = "0.5", custom_phones: dict = None) -> str:
        import pronouncing
        import string
        import json
    
        # Initialize variables
        target = target.lower().strip(string.punctuation)
        min_similarity = float(min_similarity)
        suggestions = []
        valid_words = []
        invalid_words = []
        words = []
        target_phones = ""
        word_phones = ""
        word = ""
        similarity_result = {}
    
        # Parse JSON string to list
        try:
            words = json.loads(word_list_str)
        except json.JSONDecodeError:
            return json.dumps({
                "error": "Invalid JSON string for word_list_str",
                "suggestions": []
            }, indent=2)
        
        # Get target pronunciation
        target_phones = self._get_word_phones(target, custom_phones)
        if not target_phones:
            return json.dumps({
                "error": f"Target word '{target}' not found in dictionary or custom phones",
                "suggestions": []
            }, indent=2)
    
        # Filter word list
        for word in words:
            word = word.lower().strip(string.punctuation)
            if self._get_word_phones(word, custom_phones):
                valid_words.append(word)
            else:
                invalid_words.append(word)
    
        if not valid_words:
            return json.dumps({
                "error": "No valid words found in dictionary or custom phones",
                "invalid_words": invalid_words,
                "suggestions": []
            }, indent=2)
    
        # Check each word
        for word in valid_words:
            word_phones = self._get_word_phones(word, custom_phones)
            if word_phones:
                similarity_result = self._calculate_similarity(word, word_phones, target, target_phones)
            
                if similarity_result["similarity"] >= min_similarity:
                    suggestions.append({
                        "word": word,
                        "similarity": similarity_result["similarity"],
                        "rhyme_score": similarity_result["rhyme_score"],
                        "phone_sequence_score": similarity_result["phone_sequence_score"],
                        "length_score": similarity_result["length_score"],
                        "phones": word_phones,
                        "is_custom": word in custom_phones if custom_phones else False,
                        "details": similarity_result["details"]
                    })
    
        # Sort by similarity score descending
        suggestions.sort(key=lambda x: x["similarity"], reverse=True)
    
        result = {
            "target": target,
            "target_phones": target_phones,
            "invalid_words": invalid_words,
            "suggestions": suggestions
        }
    
        return json.dumps(result, indent=2)


    def __init__(self, *args, **kwargs):
        self.is_initialized = False